Technology

Abbott launches its first over-the-counter continuous glucose monitor in the U.S.

Published

1 year ago

September 5, 2024

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A man wearing Abbott’s Lingo biosensor.

Courtesy of Abbott

Abbott Laboratories announced Thursday its over-the-counter continuous glucose monitor Lingo is available in the U.S. starting at $49.

Lingo is part of an emerging class of consumer-friendly biosensors that people can use to learn how their bodies respond to food, exercise, sleep and stress. These devices, called continuous glucose monitors, are small sensors that stick through the skin to measure real-time glucose levels. Glucose is a sugar molecule that comes from food, and it’s the body’s main energy source.

Continuous glucose monitors have served as tools for patients with diabetes, but Lingo is not intended for diabetes management. Instead, it’s designed for adults who do not take insulin and want to “improve their overall health and wellness,” according to a release.

Everyone’s glucose levels fluctuate, but consistently high levels can cause more serious health problems like metabolic disease, insulin resistance and heart disease, Abbott said. The company argues Lingo can educate users about existing habits and help them learn to manage their glucose in healthier ways.

“That’s really the goal, is to not only see and understand what’s happening inside your body, but to be able to improve on that, to be able to build these healthy habits that drive those changes,” Ben Fohner, the director of Abbott’s Lingo app, told CNBC in an interview.

Abbott already offers continuous glucose monitors for diabetes patients in the U.S., so the company is looking to break into an entirely new market with Lingo. About 1 in 3 Americans have prediabetes, for instance, but these patients typically don’t qualify for prescriptions or insurance coverage for the monitors.

Now, they can pay for the sensors out of pocket without a prescription. Users can buy one sensor online for $49, two sensors for $89 or six sensors for $249, Abbott said. Each sensor is worn on the upper arm for up to 14 days.

Olivier Ropars, Abbott’s divisional vice president of Lingo, said the company decided to offer three different pricing options so curious consumers won’t feel intimidated by a lengthy commitment. A customer can opt to buy just one sensor to try for a couple of weeks.

“We want to make it as accessible and affordable as possible,” Ropars told CNBC in an interview.

Abbott’s competitor, Dexcom, is also eyeing the prediabetes market. The company released its over-the-counter continuous glucose monitor geared toward this demographic in late August. Dexcom’s device is called Stelo, and is available in the U.S. for $89 a month. Patients with Type 2 diabetes who do not take insulin can also use it, the company said.

The U.S. Food and Drug Administration approved Dexcom’s Stelo in March, and it cleared two over-the-counter continuous glucose monitoring systems from Abbott in June. One of Abbott’s systems was Lingo, and the second system, called Libre Rio, is intended for patients with Type 2 diabetes who do not take insulin.

Though Type 2 patients who are not taking insulin could technically use Lingo, Ropars said Abbott’s recommendation is to primarily use Libre Rio since it is specifically designed for them. The company declined to share when Libre Rio will be available.

The Lingo app

Abbott’s Lingo app.

Courtesy of Abbott

Like many continuous glucose monitors, Lingo transmits data wirelessly to an app. When users open it, they’ll see a real-time reading of their glucose data that’s updated every minute.

Those glucose readings are plotted on a graph, which includes a shaded area to indicate a “healthy range.” Fohner said Abbott’s clinical team defines this range as 140 milligrams per deciliter to 70 milligrams per deciliter.

One of Abbott’s primary goals is to help Lingo users learn about glucose spikes, which occur when the amount of sugar present in the bloodstream rapidly increases and then decreases. Glucose spikes commonly occur after eating.

Spikes can push a user’s glucose reading above the healthy range, but they can also occur within the healthy range. Limiting spikes and improving glucose management overall can help users improve their sleep and mood, manage their weight, and be proactive about their future health, Abbott said.

To help users conceptualize the impact of their spikes, Abbott created a metric called the “Lingo Count.” It’s an algorithm that assigns a numeric value to each glucose spike, and it’s supposed to represent how significant the impact is. Over each day, users have a target Lingo Count that they want to aim to stay below.

Abbott’s Lingo app.

Courtesy of Abbott

Users can see this data represented on a second, more interactive glucose graph when they scroll down Lingo’s home page. A number will appear in the shaded area beneath a spike, which represents the Lingo Count for that spike.

“It’s unique to Lingo, but really that number is an indicator and a function of, how high did your spike go, how long did it last, and what was the impact that that spike had on your body,” Fohner said.

Users can analyze Lingo Count data and see how they are doing over time, as well as what time of day they tend to experience the most dramatic spikes. They can also participate in challenges and access educational resources to learn how to reduce those spikes.

Ropars said metabolism doesn’t change overnight, and everyone’s bodies work differently. He said Lingo can serve as a window into how and why a user’s glucose levels vary. But the real value of Lingo, Ropars said, is the support it can offer users as they try to establish healthy habits.

“A lot of our products today are geared toward helping people that are experiencing a chronic disease or sickness and trying to get back on track,” he said. “Here, this is the first time we’re doing a product that is helping people, improving their daily life, taking control of their health before they get sick”

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Technology

CNBC Daily Open: A murky past and uncertain future trouble traders

Published

5 hours ago

November 14, 2025

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CNBC Daily Open: A murky past and uncertain future trouble traders

Traders work on the floor of the New York Stock Exchange (NYSE) on Nov. 13, 2025 in New York City.

Spencer Platt | Getty Images

U.S. markets had their worst day since Oct. 10. That marks a sharp reversal for the Dow Jones Industrial Average, which shed 1.65% to settle at 47,457.22, a day after it closed above 48,000 for the first time. Meanwhile, the S&P 500 lost 1.66% and the Nasdaq Composite tumbled 2.29%.

The slump in stocks can partly be traced to a turnaround in sentiment regarding artificial intelligence. Tech behemoths such as Nvidia, Broadcom and Oracle slumped, with the last losing more than one-third in value since it rocketed 36% in September.

Investors, it seems, are growing worried over the high valuations of tech names, as well as the gigantic amount of capital expenditure they are committing to — with some, like Oracle, having to take on debt to fulfil those obligations.

Uncertainty over an interest rate cut in December is also putting a downer on Wall Street. It’s a coin toss as to whether the U.S. Federal Reserve will ease monetary policy then, according to the CME FedWatch tool. That’s a huge difference from a month ago, when traders were pricing in a 95.5% chance of a December cut.

Not having October’s employment and inflation numbers, and possibly never getting them, means the Fed lacks visibility into the state of the economy — and whether it should try to support the labor market or continue reining in inflation.

After all, flying blind makes it hard to see where you’ll land. As of now, that applies both to the Fed and investors trying to navigate the still-hazy ambitions of tech companies.

What you need to know today

And finally…

Tan Su Shan, chief executive officer of DBS Group Holdings Ltd., speaking at the Singapore Fintech Festival in Singapore, on Nov. 12, 2025.

Bloomberg | Bloomberg | Getty Images

CEO of Southeast Asia’s largest bank says AI adoption already paying off: ‘It’s not hope, it’s now’

“The proliferation of generative AI has been transformative for us,” DBS CEO Tan Su Shan told CNBC on the sidelines of Singapore Fintech Week. She adding that the company was experiencing a “snowballing effect” of benefits thanks to machine learning.

Tan expects AI adoption to bring DBS an overall revenue bump of more than 1 billion Singapore dollars (about $768 million) this year, compared to SG$750 million in 2024. That assessment is based on about 370 AI use cases powered by over 1,500 models throughout its business.

— Dylan Butts

Technology

‘Vibe revenue’: AI companies admit they’re worried about a bubble

Published

6 hours ago

November 14, 2025

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‘Vibe revenue’: AI companies admit they’re worried about a bubble

Eakarat Buanoi | Istock | Getty Images

LISBON, Portugal — Top tech executives told CNBC they’re concerned about a bubble forming in the artificial intelligence sector, underscoring growing unease within the industry over soaring valuation.

In recent weeks, markets have been reckoning with the notion that too much capital is pouring into the AI boom, clouding the outlook on revenue and actual profit and putting high valuations into question.

Up to now, warnings around overstretched valuations have mostly come from investors and leaders in the world of finance. Goldman Sachs’ David Solomon and Morgan Stanley’s Ted Pick have warned of potential corrections as valuations of some major tech firms reached historic highs.

The concerns have been crystallized by famed ‘Big Short’ investor Michael Burry, who this week accused major AI infrastructure and cloud providers, or ‘hyperscalers’ of understating depreciation expenses on chips. Burry warned that profits at the likes of Oracle and Meta may be vastly overstated. He recently disclosed put options that bet against Nvidia and Palantir.

However, CEOs of companies who are themselves developing AI, expressed their concerns this week during interviews with CNBC at the Web Summit tech conference in Lisbon.

“I think the evaluations are pretty exaggerated here and there, and I think there is signs of a bubble on the horizon,” Jarek Kutylowski, CEO of German AI firm DeepL, told CNBC on Tuesday.

DeepL CEO: Signs of AI bubble on the horizon

The sentiment was echoed by Picsart CEO Hovhannes Avoyan.

“We see lots of AI companies raising … tremendous valuations … without any revenue,” Avoyan told CNBC on Tuesday, adding that it is a “concern.”

The market values smaller startups with “just some noise and vibe revenue,” he said, referring to companies being backed even though they have minimal sales.

Vibe revenue is a play on “vibe coding,” a term that refers to using AI to code without needing deep technical expertise.

AI demand growing

Even with concerns over valuations, the technology industry remains bullish on the long term potential of AI.

Lyft CEO David Risher said there are reasons to be optimistic given the potential impact of AI but acknowledged the risks.

“Let’s be clear, we are absolutely in a financial bubble. There is no question, right? Because this is incredible, transformational technology. No one wants to be left behind.”

Risher went on to argue that there is a difference between the financial bubble and the industrial outlook.

“The data centers and all the model creation, all of that is going to have a long, long life, because it’s transformational. It makes people’s lives easier. It makes people’s lives better… On the other hand, you know, the financial side, it’s a little risky right now.”

The tech CEOs also addressed their outlook on AI demand for 2026 from businesses, as investors look for any clues as to what this will look like.

“I think there’s a lot of demand, and there’s a lot of interest. I think everybody understands that AI can do magical things to businesses, and… we can all operate on another level when it comes to efficiency,” Kutylowski said.

Still, businesses are “strugging in adopting” AI. “We’re going to get further, but I don’t think we’re that we’re going to be in a place where we can say, like every enterprise, every organization, has it figured out totally,” Kutylowski said.

Picsart CEO: Market values smaller startups with vibe revenue

DeepL’s core product is an AI translation tool but it recently launched a more general purpose “agent” designed to be able to carry out tasks on behalf of employees.

Francois Chadwick, the chief financial officer of Cohere, a company that is also focused on enterprise AI, told CNBC on Tuesday that “demand is definitely there.”

$4 trillion capex outlook

Despite the concerns over overstretched valuations and huge capex spend, the investment into artificial intelligence doesn’t appear to be slowing down. A report from venture capital group Accel released this week showed that the buildout of new AI data center capacity is forecast to reach 117 gigawatts by 2030 which translates into about $4 trillion worth of capital expenditure over the next 5 years.

About $3.1 trillion worth of revenue is required to pay back that capex, according to the Accel report.

Already this year, there have been a slew of deals worth billions announced by the likes of Nvidia and OpenAI as they look to develop data center capacity around the world in a bid to keep up with demand.

Philippe Botteri, a partner at Accel, said that three major factors will drive that revenue — more powerful AI models that require capacity to be trained, the use of new AI services and the “agentic revolution in the enterprise.”

“Agentic” is often a term used to describe a type of AI tool that can automatically carry out tasks on behalf of users.

Probably over-exuberance around data centers, says investor

But not everyone believes that the large amount of spending is necessary.

Ben Harburg, managing partner at Novo Capital says the figures being discussed by large tech firms for future investment may be overblown.

“We hear these crazy headline numbers about how much energy is going to be needed, how many chips are going to be needed, although, again, I think that there is probably more of a bubble brewing there than on kind of the front end, the actual product front,” Harburg told CNBC on Tuesday.

“I think we’re starting to realize that there’s been probably over exuberance around data centers. Even Sam [Altman], I think, would privately admit that they need fewer chips than they originally set out, they need less capital than they originally set out. They need less energy than they originally set out.”

Technology

CEO of Southeast Asia’s largest bank says AI adoption already paying off: ‘It’s not hope, it’s now’

Published

9 hours ago

November 14, 2025

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CEO of Southeast Asia's largest bank says AI adoption already paying off: ‘It’s not hope, it’s now’

Tan Su Shan, chief executive officer of DBS Group Holdings Ltd., speaking at the Singapore Fintech Festival in Singapore, on Nov. 12, 2025.

Bloomberg | Bloomberg | Getty Images

SINGAPORE – Amid fears of an artificial intelligence bubble, much has been made of recent reports suggesting that AI has yet to generate returns for companies investing billions into adopting the tech.

But that’s not what the chief executive of Southeast Asia’s largest bank is seeing — she says her firm is already reaping the rewards of its AI initiatives, and it’s only just the beginning.

“It’s not hope. It’s now. It’s already happening. And it will get even better,” DBS CEO Tan Su Shan told CNBC on the sidelines of Singapore Fintech Week, when asked about the promise of AI adoption.

DBS has been working to implement artificial intelligence across its bank for over a decade, which helped prepare its internal data analytics for recent waves of generative and agentic AI.

Agentic AI is a type of artificial intelligence that relies on data to proactively make independent decisions, plan and execute tasks autonomously, with minimal human oversight.

“The proliferation of generative AI has been transformative for us,” Tan said, adding that the company was experiencing a “snowballing effect” of benefits thanks to machine learning.

A major area in which DBS has applied AI is in its financial services to institutional clients, with AI used to collect and leverage data for clients in order to better contextualize and personalize offerings.

According to Tan, this has resulted in “faster and more resilient” teams. The CEO believes that these uses of AI have contributed to a recent uptick in the bank’s deposit growth as compared to competitors’.

The company also recently launched a newly enhanced AI-powered assistant for corporate clients known as “DBS Joy,” which assists clients with unique corporate banking queries around the clock.

ROI concerns

Despite Tan’s strong convictions about AI, recent evidence suggests that many companies are struggling to turn their AI investments into tangible profits.

MIT released a report in July that found 95% of 300 publicly disclosed AI initiatives, encompassing generative AI investments of $30–$40 billion, had failed to achieve real returns.

However, at least in the banking sector, there are signs that the tides are turning.

While DBS doesn’t differentiate spending in generative AI from other in-house investments, other major banks have recently offered this comparison.

JPMorgan Chase CEO Jamie Dimon stated in an interview with Bloomberg TV last month that the bank is already breaking even on its approximately $2 billion of annual investments in AI adoption. That represents “just the tip of the iceberg,” he added.

Those expectations are shared by DBS, which plans to continue to accelerate its AI development to become an AI-powered bank.

The ultimate goal, according to Tan, is for its generative AI to develop into a trusted financial advisor for clients, including retail users who are expected to interact with personalized AI agents through the DBS banking app.

The bank already has over 100 AI algorithms that analyze users’ data to provide them with personalized “nudges,” such as alerts on incoming shortfalls, product recommendations, and other insights.

Continued AI investments

While DBS may already be reaping rewards from its AI adoption, Tan acknowledged that it will require continued investments, not only in capital, but in the time needed to reskill employees.

The company has launched several AI reskilling initiatives across departments this year and has even deployed a generative AI-powered coaching tool to support these efforts.

This will help the company automate mundane work and refocus its staff on building and maintaining human-to-human relationships with customers, rather than reducing headcount, Tan said.